Luc Canard

854 total citations
9 papers, 684 citations indexed

About

Luc Canard is a scholar working on Molecular Biology, Materials Chemistry and Spectroscopy. According to data from OpenAlex, Luc Canard has authored 9 papers receiving a total of 684 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 4 papers in Materials Chemistry and 3 papers in Spectroscopy. Recurrent topics in Luc Canard's work include Protein Structure and Dynamics (5 papers), Enzyme Structure and Function (4 papers) and Machine Learning in Bioinformatics (2 papers). Luc Canard is often cited by papers focused on Protein Structure and Dynamics (5 papers), Enzyme Structure and Function (4 papers) and Machine Learning in Bioinformatics (2 papers). Luc Canard collaborates with scholars based in France, United Kingdom and United States. Luc Canard's co-authors include J.-P. Mornon, Isabelle Callebaut, Patrick Durand, Gilles Labesse, Anne Poupon, Bernard Henrissat, Jacques Chomilier, Luis Enrique Donate, Tom L. Blundell and Tom L. Blundell and has published in prestigious journals such as Journal of Molecular Biology, Nature Reviews Drug Discovery and International Journal of Molecular Sciences.

In The Last Decade

Luc Canard

9 papers receiving 670 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Luc Canard France	7	513	174	83	54	50	9	684
Jonathan King United States	10	641 1.2×	168 1.0×	40 0.5×	68 1.3×	66 1.3×	16	760
Maurício G. S. Costa Brazil	17	422 0.8×	84 0.5×	60 0.7×	37 0.7×	24 0.5×	38	681
Daphne H. E. W. Huberts Netherlands	9	618 1.2×	71 0.4×	63 0.8×	74 1.4×	38 0.8×	15	815
Nicolas Lentze Switzerland	9	571 1.1×	82 0.5×	78 0.9×	110 2.0×	24 0.5×	11	689
P. McNeil United Kingdom	3	460 0.9×	126 0.7×	30 0.4×	37 0.7×	18 0.4×	4	558
Deqiang Yao China	16	512 1.0×	88 0.5×	137 1.7×	99 1.8×	30 0.6×	40	817
Coos Baakman Netherlands	7	799 1.6×	183 1.1×	39 0.5×	51 0.9×	68 1.4×	10	1.0k
Marc S. Sherman United States	6	487 0.9×	50 0.3×	86 1.0×	79 1.5×	23 0.5×	18	648
Steven Beasley United States	13	634 1.2×	213 1.2×	65 0.8×	49 0.9×	44 0.9×	18	814
Cesira de Chiara United Kingdom	17	630 1.2×	99 0.6×	41 0.5×	56 1.0×	25 0.5×	29	761

Countries citing papers authored by Luc Canard

Since Specialization

Citations

This map shows the geographic impact of Luc Canard's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Luc Canard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luc Canard more than expected).

Fields of papers citing papers by Luc Canard

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Luc Canard. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Luc Canard. The network helps show where Luc Canard may publish in the future.

Co-authorship network of co-authors of Luc Canard

This figure shows the co-authorship network connecting the top 25 collaborators of Luc Canard. A scholar is included among the top collaborators of Luc Canard based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Luc Canard. Luc Canard is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

Berthelot, Karine, et al.. (2022). 81 T cell stimulation assay and immunoassays comparison for soluble cytokines profiling in drug discovery. Regular and Young Investigator Award Abstracts. A88–A88. 1 indexed citations

Kodamullil, Alpha Tom, et al.. (2017). Tracing investment in drug development for Alzheimer disease. Nature Reviews Drug Discovery. 16(12). 819–819. 38 indexed citations

Hofmann‐Apitius, Martin, G. C. Ball, Stephan Gebel, et al.. (2015). Bioinformatics Mining and Modeling Methods for the Identification of Disease Mechanisms in Neurodegenerative Disorders. International Journal of Molecular Sciences. 16(12). 29179–29206. 38 indexed citations

Canard, Luc, et al.. (2003). Non‐intertwined binary patterns of hydrophobic/nonhydrophobic amino acids are considerably better markers of regular secondary structures than nonconstrained patterns. Proteins Structure Function and Bioinformatics. 51(2). 236–244. 22 indexed citations

Donate, Luis Enrique, et al.. (1997). Predicting the conformational class of short and medium size loops connecting regular secondary structures: application to comparative modelling. Journal of Molecular Biology. 267(2). 352–367. 61 indexed citations

Durand, Philippe, Luc Canard, & J.-P. Mornon. (1997). Visual BLAST and Visual FASTA: graphic workbenches for interactive analysis of full BLAST and FASTA outputs under Microsoft Windows 95/NT. Computer applications in the biosciences. 13(4). 407–413. 18 indexed citations

Callebaut, Isabelle, Gilles Labesse, Patrick Durand, et al.. (1997). Deciphering protein sequence information through hydrophobic cluster analysis (HCA): current status and perspectives. Cellular and Molecular Life Sciences. 53(8). 621–645. 414 indexed citations

Donate, Luis Enrique, et al.. (1996). Conformational analysis and clustering of short and medium size loops connecting regular secondary structures: A database for modeling and prediction. Protein Science. 5(12). 2600–2616. 87 indexed citations

Canard, Luc, et al.. (1996). Analysis, clustering and prediction of the conformation of short and medium size loops connecting regular secondary structures.. PubMed. 570–89. 5 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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